To increase utility, machines, such as computers, are called upon to classify or organize content items to an ever increasing extent. For example, some classification methods referred to as “machine learning algorithms” are used to organize content items into a predefined structure based on attributes thereof or external parameters. The classification methods may also be used to route the content items to appropriate individuals (e.g., users on a network) and/or locations (e.g., in a computer memory, in a communications network, etc.). For example, an information service, such as a web portal, may implement the classification methods to classify and provide customized delivery of the content items to users. That is, a user may register with the web portal and indicate an interest in the New York Mets®. Using the classification methods, the web portal may identify and select the content items available on the Internet, such as news stories, product offers, etc., which are related to the Mets and deliver the selected content items to the user.
Similarly, the classification methods may be used to filter out undesired content. Unwanted and/or unsolicited email (“spam”) is generally a nuisance, using storage space and potentially delivering harmful content (e.g., viruses, worms, Trojan horses, etc.). If the user is required to manually filter the spam from the desired content, the user may not register with the web portal. If users refrain from using the web portal, a total audience size may shrink and, ultimately, a decrease in advertising and/or partnership revenue may occur. Thus, the web portal may implement the classification methods to identify and filter out the spam.
Due to an ever-increasing amount of content available on the Internet (and in private networks) and a desire by users to have the presentation of customized content and network interfaces, there exists a need for efficient and accurate classification methods.